Strategy Acquisition for the Game "Othello" Based on Reinforcement Learning

@inproceedings{Yoshioka1998StrategyAF,
  title={Strategy Acquisition for the Game "Othello" Based on Reinforcement Learning},
  author={Taku Yoshioka and Shin Ishii and Minoru Ito},
  booktitle={ICONIP},
  year={1998}
}
This article discusses automatic strategy acquisition for the game \Othello" based on reinforcement learning. In our approach, two computer players initially know only the game rules, but they become relatively stronger after playing several thousands of games against each other. In each game, the players re ne the evaluation function for the game state, which is achieved in a reinforcement learning manner. Since the state space is very large, we employ an RBF (Radial Basis Functions) network… CONTINUE READING
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Knight- Cap: A chess program that learns by combining TD( ) with minimax search,

  • J. Baxter, A. Tridgell, L. Weaver
  • Technical Report,
  • 1997
2 Excerpts

Strategy acquisition of the game based on the reinforcement learning," ATR Technical Report, TR-H-159

  • M. Hayashi, S. Ishii
  • Kyoto: ATR,
  • 1995
1 Excerpt

Practical issues in temporal di erence learning,

  • G. Tesauro
  • Machine Learning,
  • 1992
2 Excerpts

Technical note: Qlearning

  • Watkins, C.J.C.H, P. Dayan
  • Machine Learning,
  • 1992
1 Excerpt

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